Setup & Introduction

Introducation: R

• R is a programming language specifically designed for statistical computing and data analysis.
• It was created by statisticians and data analysts for tasks ranging from basic data manipulation to advanced statistical modeling.
• Widely used in academia, industry, and research for its flexibility and extensive package ecosystem.

R Key Features

• Open-source and freely available.
• Rich statistical and graphical capabilities.
• Active and supportive user community.
• Cross-platform compatibility (Windows, macOS, Linux).

R Use Cases

• Data cleaning and manipulation.
• Statistical analysis and hypothesis testing.
• Data visualization with customizable plots.

Installing R

• If you already have R and RStudio, reinstall the latest version is recommended

RStudio: IDE for R

Overview

• RStudio is an integrated development environment (IDE) that enhances the R programming experience.
• It provides a user-friendly interface, making it easier to write, test, and debug R code.

Workflow

• Creating and running scripts.
• Managing projects for better organization.
• Utilizing the built-in version control (Git).

RStudio Key Features

• Script Editor: Write and execute R scripts.
• Console: Interact with R in real-time.
• Environment Pane: View and manage objects in your workspace.
• Plots Pane: Instantly visualize data and plots.
• Packages and Help: Easily install and access R packages.

Quarto

What is Quarto?

• Open-source scientific and technical publishing system
• Author can use any favourite editor (RStudio, Jupyter & VScode)
• Create dynamic content with R, Python, Julia & Observable
• Publish reproducible, production quality articles, presentations, dashboards, websites, blogs, and books in HTML, PDF, MS Word, ePub, and more.
• Write using Pandoc markdown, including equations, citations, crossrefs, figure panels, callouts, advanced layout, and more.

Quarto Advantage

• Reproducibility: Easily reproduce analyses with the same code and data.
• Communication: Share insights with colleagues and stakeholders by creating reports and documents.
• Flexibility: Create interactive documents, presentations, and dashboards.

Before we start

• Different people may use R and RStudio differently
• Having a sensible workflow can improve you work

Workflow thinking

• treat individual R process and the associated workspace is disposable
• dont treat your workspace as a pet, i.e. it hold precious objects and you arent 100% sure you can reproduce them.
• if you have this attachment, that inidcate you have a non-reproducible workflow.

further reading: https://rstats.wtf/

Prerequisite for workflow thinking

• Use IDE.
  • Use ID with proper support for project
• Always start R with blank state.
  • when quit R, do not save workspace to an .Rdata file.
  • when launch R, do not reload the workspace from .Rdata file.
• Restart R often during development.
  • avoid rm(list = ls())
  • develop cripts in fresh R process